Lead AIML Software Engineer (Python)

Overview

As Lead Software Engineer in the AI and Machine Learning Data Platforms team, you drive secure, scalable technology solutions that support the firm’s objectives. You will lead technical work across multiple domains, mentor junior engineers, and shape data-driven products with cross-functional partners. You’ll champion enterprise AI-assisted development practices to improve quality, speed, and reliability, while ensuring secure and compliant delivery. This role offers impact at scale within a trusted financial services environment, blending hands-on coding with technical leadership.

Responsibilities

• Develop secure, high-quality production code and review others code
• Lead evaluation sessions with vendors and internal teams to assess architectural designs
• Provide technical leadership on data projects across engineers, product managers, and stakeholders
• Mentor and guide junior engineers
• Drive adoption of enterprise AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes
• Establish validation standards (secure coding, peer review, automated testing) and promote reusable patterns
• Leverage SDLC tools and AI-assisted development and automation to enhance automation value
• Identify opportunities to automate recurring issues to improve operational stability

Key requirements

• Formal training or certification on software engineering concepts
• Hands-on experience delivering system design, development, testing, and operational stability
• Strong experience in a cloud-based engineering environment
• Advanced Python; other programming languages a plus
• Experience leading effective use of AI-assisted software development tools with ability to set team expectations for correct, performant, secure outputs
• Strong understanding of responsible AI use in engineering workflows, data sensitivity, and secure handling
• Proficient in all aspects of the Software Development Life Cycle
• Good understanding of databases/data structures
• Knowledge of agile methodologies (CI/CD, Application Resiliency, Security)
• In-depth knowledge of the financial services industry and IT systems
• Practical cloud-native experience
• leadership
• mentorship
• cross-functional collaboration
• Python (Advanced)
• cloud-native engineering
• AI-assisted development tools (coding, code review, test acceleration, troubleshooting)

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